Tinghui Xu,Jiwei Zhao
Tinghui Xu
Causal inference plays a crucial role in biomedical studies and social sciences. Over the years, researchers have devised various methods to facilitate causal inference, particularly in observational studies. Among these methods, the doubly...
Robust analyzes for longitudinal clinical trials with missing and non-normal continuous outcomes [0.03%]
具有缺失和非正态连续结果的纵向临床试验的稳健分析方法
Siyi Liu,Yilong Zhang,Gregory T Golm et al.
Siyi Liu et al.
Missing data is unavoidable in longitudinal clinical trials, and outcomes are not always normally distributed. In the presence of outliers or heavy-tailed distributions, the conventional multiple imputation with the mixed model with repeate...
Robust Variance Estimation for Covariate-Adjusted Unconditional Treatment Effect in Randomized Clinical Trials with Binary Outcomes [0.03%]
随机对照试验中调整协变量的二元指标无条件效应的稳健方差估计方法研究
Ting Ye,Marlena Bannick,Yanyao Yi et al.
Ting Ye et al.
To improve precision of estimation and power of testing hypothesis for an unconditional treatment effect in randomized clinical trials with binary outcomes, researchers and regulatory agencies recommend using g-computation as a reliable met...
W Jenny Shi,Jan Hannig,Randy C S Lai et al.
W Jenny Shi et al.
As a classical problem, covariance estimation has drawn much attention from the statistical community for decades. Much work has been done under the frequentist and the Bayesian frameworks. Aiming to quantify the uncertainty of the estimato...
Interval Estimation for Minimal Clinically Important Difference and its Classification Error via a Bootstrap Scheme [0.03%]
一种基于Bootstrap的估计最小临床重要差异及其分类误差点区间的方法
Zehua Zhou,Jiwei Zhao,Melissa Kluczynski
Zehua Zhou
With the improved knowledge on clinical relevance and more convenient access to the patient-reported outcome data, clinical researchers prefer to adopt minimal clinically important difference (MCID) rather than statistical significance as a...
RESPONSE TO DISCUSSION OF 'NUTRITIONAL EPIDEMIOLOGY METHODS AND RELATED STATISTICAL CHALLENGES AND OPPORTUNITIES' [0.03%]
对“营养流行病学方法及统计挑战和机遇”的讨论答复
Ross L Prentice,Ying Huang
Ross L Prentice
Nutritional Epidemiology Methods and Related Statistical Challenges and Opportunities [0.03%]
营养流行病学方法及相关的统计挑战和机遇
Ross L Prentice,Ying Huang
Ross L Prentice
The public health importance of nutritional epidemiology research is discussed, along with methodologic challenges to obtaining reliable information on dietary approaches to chronic disease prevention. Measurement issues in assessing dietar...
Shuhan Liang,Wenbin Lu,Rui Song
Shuhan Liang
Recently deep learning has successfully achieved state-of-the-art performance on many difficult tasks. Deep neural network outperforms many existing popular methods in the field of reinforcement learning. It can also identify important cova...